Data Science Dojo

JUNE 1, 2023

Machine Learning for Absolute Beginners by Kirill Eremenko and Hadelin de Ponteves This is another beginner-level course that teaches you the basics of machine learning using Python. The course covers topics such as supervised learning, unsupervised learning, and reinforcement learning.

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Pickl AI

NOVEMBER 4, 2024

This article will guide you through effective strategies to learn Python for Data Science, covering essential resources, libraries, and practical applications to kickstart your journey in this thriving field. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. in 2022, according to the PYPL Index.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Smart Data Collective

JUNE 4, 2021

it is overwhelming to learn data science concepts and a general-purpose language like python at the same time. Exploratory Data Analysis. Exploratory data analysis is analyzing and understanding data. For exploratory data analysis use graphs and statistical parameters mean, medium, variance.

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Data Science Exploratory Data Analysis Machine Learning Machine Learning 133

IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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Pickl AI

NOVEMBER 13, 2024

Summary: Machine Learning is categorised into four main types: supervised, unsupervised, semi-supervised, and Reinforcement Learning. Each type employs distinct methodologies for Data Analysis and decision-making. UnSupervised Learning uncovers hidden patterns in unlabelled datasets.

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Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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Dataconomy

APRIL 18, 2023

Undetectable backdoors can be implemented in any ML algorithm Machine learning Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that can learn from data and make predictions or decisions.

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Pickl AI

AUGUST 1, 2023

The different algorithms used for text mining are: Naive Bayes: A probabilistic algorithm used for text classification and sentiment analysis. Support Vector Machines (SVM): A supervised learning algorithm used for text classification and document clustering. So, don’t delay your growth journey and connect with Pickl.AI

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ODSC - Open Data Science

OCTOBER 3, 2023

Data Analysis and Interpretation Data plays a critical role in prompt engineering. To excel in this field, you need a diverse skill set that can include a profound understanding of AI models, linguistic expertise, creative problem-solving skills, data analysis capabilities, and strong communication and collaboration skills.

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Pickl AI

OCTOBER 9, 2023

This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming. Unsupervised learning algorithms Unsupervised learning algorithms are a vital part of Machine Learning, used to uncover patterns and insights from unlabeled data.

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Towards AI

JANUARY 10, 2024

Task Orientation How were we doing machine learning almost a year ago? They are called foundation models because, with that wide set of data, you build foundations that need not change every time you adapt it to a specific business use case. And they can handle multiple types of data (images, text, video, and audio).

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Pickl AI

JULY 17, 2023

The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Unsupervised Learning Algorithms Unsupervised Learning Algorithms tend to perform more complex processing tasks in comparison to supervised learning.

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Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Becoming Human

MAY 15, 2023

These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey. Data Analysis After learning math now, you are able to talk with your data.

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Data Science Dojo

JUNE 11, 2024

They are also known as threshold logic units (TLUs) and serve as a supervised learning algorithm that classifies data into two categories, making them a binary classifier. Moreover, they possess the risk of overfitting. Despite these limitations, shallow neural networks are a useful resource.

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DrivenData Labs

FEBRUARY 3, 2025

Recently, I became interested in machine learning, so I was enrolled in the Yandex School of Data Analysis and Computer Science Center. Machine learning is my passion and I often participate in competitions. To increase the amount of data, I tried to generate data using some LLMs in a few-shot way.

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Pickl AI

FEBRUARY 22, 2024

Summary: Dive into programs at Duke University, MIT, and more, covering Data Analysis, Statistical quality control, and integrating Statistics with Data Science for diverse career paths. offer modules in Statistical modelling, biostatistics, and comprehensive Data Science bootcamps, ensuring practical skills and job placement.

Data Science 52

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Towards AI

APRIL 4, 2024

A sector that is currently being influenced by machine learning is the geospatial sector, through well-crafted algorithms that improve data analysis through mapping techniques such as image classification, object detection, spatial clustering, and predictive modeling, revolutionizing how we understand and interact with geographic information.

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Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. Explain the difference between supervised and unsupervised learning.

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Pickl AI

SEPTEMBER 17, 2024

Summary: Dimensionality reduction is a crucial technique in data analysis that simplifies complex datasets by reducing the number of features while retaining essential information. Dimensionality reduction in Machine Learning enhances model performance and improves data visualisation by focusing on the most significant dimensions.

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Pickl AI

OCTOBER 2, 2024

Genomic Analysis is crucial for various applications, including personalised medicine, cancer research, genetic disorder diagnosis, and evolutionary biology. AI Techniques Used in Genomic Analysis AI encompasses a range of techniques that can be applied to genomic Data Analysis.

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DataRobot Blog

DECEMBER 15, 2022

Let’s run through the process and see exactly how you can go from data to predictions. supervised learning and time series regression). Prepare your data for Time Series Forecasting. Perform exploratory data analysis. The use case will be forecasting sales for stores, which is a multi-time series problem.

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

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Pickl AI

NOVEMBER 18, 2024

The main types are supervised, unsupervised, and reinforcement learning, each with its techniques and applications. Supervised Learning In Supervised Learning , the algorithm learns from labelled data, where the input data is paired with the correct output. predicting house prices).

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Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning.

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Pickl AI

JANUARY 12, 2023

After the completion of the course, they can perform data analysis and build products using R. These include the following: Introduction to Data Science Introduction to Python SQL for Data Analysis Statistics Data Visualization with Tableau 5. Data Science Program for working professionals by Pickl.AI

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Pickl AI

FEBRUARY 12, 2024

This theorem is crucial in inferential statistics as it allows us to make inferences about the population parameters based on sample data. Differentiate between supervised and unsupervised learning algorithms. Here is a brief description of the same.

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PyImageSearch

FEBRUARY 6, 2023

But we would still apply data augmentation to ensure the model doesn’t overfit and generalize well on the test dataset. Data Analysis When working with data, especially supervised learning, it is often a best practice to check data imbalance.

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Pickl AI

FEBRUARY 7, 2025

Features : The attributes or characteristics of the data used to make predictions. Types of Machine Learning Machine Learning is divided into three main types based on how the algorithm learns from the data: Supervised Learning In supervised learning , the algorithm is trained on labelled data.

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Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

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Chatbots Life

APRIL 19, 2024

It analyzes existing data to discover patterns and generate new content. This technology employs different learning methods during training. These include unsupervised or semi-supervised learning. GANs excel in creating visual and multimedia data. Data Analysis and Insights Generative AI excels in data analysis.

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Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

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Pickl AI

DECEMBER 4, 2024

Ensuring data quality is vital for producing reliable results. Machine Learning Understanding Machine Learning algorithms is essential for predictive analytics. This includes supervised learning techniques like linear regression and unsupervised learning methods like clustering.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

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phData

MAY 19, 2023

These algorithms are not just fundamental to any data scientist’s toolkit, but they also form the backbone of many complex machine learning workflows. Understanding and mastering these techniques can unlock a deeper level of data analysis and predictive power.

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Heartbeat

OCTOBER 25, 2023

The field demands a unique combination of computational skills and biological knowledge, making it a perfect match for individuals with a data science and machine learning background.

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